According to universal approximation theorem, any continuous function can be uniformly approximated by neural network with single hidden layer.
Similarly, can a convex function $f: \mathbb{R}^n \rightarrow \mathbb{R}$ be uniformly approximated by convex combination of simpler convex functions?
Or, is there any analysis on the collection of convex functions?